A QM-CAMD approach to solvent design for optimal reaction rates. (23rd February 2017)

• Record Type: Journal Article
• Authors: Struebing, Heiko; Obermeier, Stephan; Siougkrou, Eirini; Adjiman, Claire S.; Galindo, Amparo
• Is Part Of: Chemical engineering science. Volume 159(2017)
• Page Start: 69
• Page End: 83
• Publication Date: 2017-02-23
• Subjects: Quantum mechanics -- Computer-aided molecular design -- Surrogate model -- Phase equilibrium -- Kinetics -- Group contribution; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2016.09.032
• Languages: English
• ISSNs: 0009-2509

Abstract

Abstract: The choice of solvent in which to carry out liquid-phase organic reactions often has a large impact on reaction rates and selectivity and is thus a key decision in process design. A systematic methodology for solvent design that does not require any experimental data on the effect of solvents on reaction kinetics is presented. It combines quantum mechanical computations for the reaction rate constant in various solvents with a computer-aided molecular design (CAMD) formulation. A surrogate model is used to derive an integrated design formulation that combines kinetics and other considerations such as phase equilibria, as predicted by group contribution methods. The derivation of the mixed-integer nonlinear formulation is presented step-by-step. In the application of the methodology to a classic S N 2 reaction, the Menschutkin reaction, the reaction rate is used as the key performance objective. The results highlight the trade-offs between different chemical and physical properties such as reaction rate constant, solvent density and solid reactant solubility and lead to the identification of several promising solvents to enhance reaction performance. Abstract : Graphical abstract: Abstract : Highlights: Predictive approach to solvent design, including kinetics and phase equilibrium. Combines quantum mechanical calculations with computer-aided molecular design. Promising solvents that maximize the rate of an S N 2 reaction identified. Highlights trade-off between rate constant, reactant solubility and solvent density.